Suggestions appear as you type. Use the up and down arrows to choose one and Enter to open it.

This page's audience our own tag's counts — open to see them
–Visits
–Page views
–Clicks to vendors
–Time on page
–Reading now
Clicks to vendors, by tool
  • –
Top countries
  • –
Devices
  • –

– · visits, page views and clicks counted by our own tag, which counts more than our checked analytics; every figure rounded down · how we count

Apache Storm review

A self-hosted choice for developers building fault-tolerant stream-processing topologies.

7.8/10Editor score
Apache Storm7.8 Visit Apache Storm

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Apache Storm is open-source software for distributed, real-time processing of unbounded data streams. Developers assemble applications as topologies made of spouts and bolts, using them to ingest, transform, join, aggregate, and route data. It is aimed at teams running self-hosted stream-processing clusters for analytics, ETL, continuous computation, and other real-time workloads. Deployment spans Windows, Linux, web, API, and self-hosted environments, with JavaScript, Python, Ruby, and C# listed among the supported languages.

Its main strength is breadth within a topology-based model. Storm provides fault-tolerant cluster execution, local mode for development and testing, multilang components, tumbling and sliding windows, stream joins, repartitioning, and stateful processing through Trident. The integration set covers Kafka, HBase, HDFS, Apache Iceberg, JDBC, JMS, Redis, YARN, Mesos, Docker, and Kubernetes. That combination suits systems that need continuous computation alongside connections to storage, messaging, container, and cluster infrastructure.

Apache Storm has no license cost as open-source software, but its self-hosted approach places deployment and cluster operation with the adopting organization. Teams should choose it when developers want direct control over stream topologies, stateful processing, and runtime placement. It is less suitable for groups seeking a managed service or a SQL-first stream-processing workflow, where a product centered on those operating or development preferences may be a better alternative.

Apache Storm pros and cons

  • Where it wins
    • Processes unbounded streams with fault-tolerant cluster execution
    • Supports stateful Trident processing, windows, joins, and aggregations
    • Connects with Kafka, Kubernetes, HDFS, Redis, and JDBC
  • Where it doesn't
    • Self-hosted deployment requires organizations to operate clusters
    • Topology development centers on spouts, bolts, and programming code
    • SQL-first workflows are not the natural fit for its topology model

Apache Storm fact sheet, pricing and score →

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated · How we research and update